Developing Clinically Suitable Measures of Social Cognition for Children: Initial Findings from a Normative Sample
Bibliographic record
Abstract
Our understanding of children's social competence has increased tremendously over the past two decades. There is increasing evidence to suggest that social-cognitive impairments are not restricted to children on the autistic spectrum, but rather may be associated with a host of developmental and acquired neurological conditions including learning disabilities, attention deficit disorder, traumatic brain injury, and stroke. Although many investigators have begun to bridge the gap between clinical practice and research by applying experimental tasks to clinical populations, few tools are available for the clinical evaluation of social competence, particularly in children. This study marks a series of first steps in the development of measures suitable for the assessment of children between 6 and 12 years of age. The results of the study provide data for a number of experimental tasks that have been adapted with clinical practice in mind. A discussion of the developmental progressions and the relationships among the measures is also included.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".